bow_ci: Compute bootstrap CIs for the average descriptor occurrence...

In till-tietz/rbow: Bag of Words and Document Frequency Analysis for Multiple Dictionaries

Description

Compute bootstrap CIs for the average descriptor occurrence metric of the bow_analysis function

Usage

bow_ci(
  bow_analysis_output,
  bootstraps = 1000,
  alpha = 0.95,
  window = 10,
  per_occurrence = TRUE,
  bootstrap_terms = TRUE
)

Arguments

bow_analysis_output	result list outputted by the bow_analysis function
bootstraps	number of bootstrap samples to draw (default = 1000)
alpha	alpha value to compute CIs with
window	window size used in the bow_analysis function (default = 10)
per_occurrence	per occurrence value used in the bow_analysis function (default = TRUE)
bootstrap_terms	if TRUE the bootstrap function samples the set of all terms within a window of all phenomenon occurrences. If FALSE the boostrap function samples from a vector of descriptor counts for each phenomenon occurrence.

Value

list of analzed texts. Each text list contains a data frame of observed means and CI bounds for each descriptor and phenomenon pair.

till-tietz/rbow documentation built on Oct. 21, 2021, 9:16 p.m.